509 citations
- Google (United States)US6 papers
- University of Tennessee Health Science CenterUS3 papers
- AstraZeneca (United States)US2 papers
- Beijing Normal UniversityCN2 papers
- Humboldt-Universität zu BerlinDE2 papers
- Medical University of GrazAT2 papers
- Stanford UniversityUS2 papers
- Bernstein Center for Computational Neuroscience BerlinDE1 paper
- Booz Allen Hamilton (United States)US1 paper
- Brown UniversityUS1 paper
- Bucknell UniversityUS1 paper
- East China Normal UniversityCN1 paper
Showing 2020Show all
3 papers · 1 filter
cs.CV2020★ 50 cited
Predicting Prostate Cancer-Specific Mortality with A.I.-based Gleason Grading
Ellery Wulczyn, Kunal Nagpal, Matthew Symonds +20
Gleason grading of prostate cancer is an important prognostic factor but suffers from poor reproducibility, particularly among non-subspecialist pathologists. Although artificial i…
eess.IV2020★ 233 cited
Interpretable Survival Prediction for Colorectal Cancer using Deep Learning
Ellery Wulczyn, David F. Steiner, Melissa Moran +20
Deriving interpretable prognostic features from deep-learning-based prognostic histopathology models remains a challenge. In this study, we developed a deep learning system (DLS) f…
eess.SP2020★ 6 cited
Interpretable Classification of Bacterial Raman Spectra with Knockoff Wavelets
Charmaine Chia, Matteo Sesia, Chi-Sing Ho +4
Deep neural networks and other sophisticated machine learning models are widely applied to biomedical signal data because they can detect complex patterns and compute accurate pred…